Efficient inference for expressive comparative preference languages

Show simple item record

dc.contributor.author Wilson, Nic
dc.date.accessioned 2020-11-18T12:52:39Z
dc.date.available 2020-11-18T12:52:39Z
dc.date.issued 2009-07
dc.identifier.citation Wilson, N.(2009) 'Efficient Inference for Expressive Comparative Preference Languages', IJCAI-09: Proceedings of the 21st International Joint conference on Artificial intelligence, Pasadena, California, USA, 11-17 July, pp. 961-966. en
dc.identifier.startpage 961 en
dc.identifier.endpage 966 en
dc.identifier.isbn 978-1-57735-426-0
dc.identifier.uri http://hdl.handle.net/10468/10774
dc.description.abstract A fundamental task for reasoning with preferences is the following: given input preference information from a user, and outcomes α and β, should we infer that the user will prefer α to β? For CP-nets and related comparative preference formalisms, inferring a preference of α over β using the standard definition of derived preference appears to be extremely hard, and has been proved to be PSPACE-complete in general for CP-nets. Such inference is also rather conservative, only making the assumption of transitivity. This paper defines a less conservative approach to inference which can be applied for very general forms of input. It is shown to be efficient for expressive comparative preference languages, allowing comparisons between arbitrary partial tuples (including complete assignments), and with the preferences being ceteris paribus or not. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher The Association for the Advancement of Artificial Intelligence (AAAI), The International Joint Conferences on Artificial Intelligence, Inc. (IJCAI) en
dc.relation.uri https://www.ijcai.org/Proceedings/2009
dc.rights © 2009 IJCAI; AAAI en
dc.subject CP-nets en
dc.subject Constraints en
dc.subject AI en
dc.subject Artificial intelligence en
dc.title Efficient inference for expressive comparative preference languages en
dc.type Conference item en
dc.internal.authorcontactother Nic Wilson, Computer Science, University College Cork, Cork, Ireland. +353-21-490-3000 Email: n.wilson@ucc.ie en
dc.internal.availability Full text available en
dc.date.updated 2020-11-04T13:27:01Z
dc.description.version Accepted Version en
dc.internal.rssid 52485566
dc.description.status Peer reviewed en
dc.internal.copyrightchecked No
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Pasadena, California, USA en
dc.internal.IRISemailaddress n.wilson@ucc.ie en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Principal Investigator Programme (PI)/00/PI.1/C075/IE/Constraint Computation: Automation and Application/ en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Principal Investigator Programme (PI)/08/IN.1/I1912/IE/The Development of Artificial intelligence Approaches for Preferences in Combinational Problems/ en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Strategic Research Cluster/07/SRC/I1170/IE/SRC ITOBO: Information and Communication Technology for Sustainable and Optimised Building Operation/ en

Files in this item

This item appears in the following Collection(s)

Show simple item record

This website uses cookies. By using this website, you consent to the use of cookies in accordance with the UCC Privacy and Cookies Statement. For more information about cookies and how you can disable them, visit our Privacy and Cookies statement